Temporal and Spatial Variations of Sea Surface Temperature in the East China

Continental Shelf Research 20 (2000) 373}387

Temporal and spatial variations of sea surface temperature in the East China Sea Chente Tseng*, Chiyuan Lin, Shihchin Chen, Chungzen Shyu Department of Fishery Information, Taiwan Fisheries Research Institute, Keelung, Taiwan, ROC

Abstract

Sea surface temperature of the East China Sea (ECS) were analyzed using the NOAA/AVHRR SST images. These satellite images reveal surface features of ECS including mainly the Kuroshio Current, Kuroshio Branch Current, Taiwan Warm Current, China coastal water, Changjiang diluted water and Yellow Sea mixed cold water. The SST of ECS ranges from 27 to 293C in summer; some cold eddies were found o! northeast Taiwan and to the south of Changjiang mouth. SST anomalies at the center of these eddies were about 2}53C. The strongest front usually occurs in May each year and its temperature gradient is about 5}63C over a cross-shelf distance of 30 nautical miles. The Yellow Sea mixed cold water also provides a contrast from China Coastal waters shoreward of the 50 m isobath; cross-shore temperature gradient is about 6}83C over 30 nautical miles. The Kuroshio intrudes into ECS preferably at two locations. The "rst is o! northeast Taiwan; the subsurface water of Kuroshio is upwelled onto the shelf while the main current is de#ected seaward. The second site is located at 313N and 1283E, which is generally considered as the origin of the Tsushima Warm Current. More quantitatively, a 2-year time series of monthly SST images is examined using EOF analysis to determine the spatial and temporal variations in the northwestern portion of ECS. The "rst spatial EOF mode accounts for 47.4% of total spatial variance and reveals the Changjiang plume and coastal cold waters o! China. The second and third EOF modes account for 16.4 and 9.6% of total variance, respectively, and their eigenvector images show the intrusion of Yellow Sea mixed cold waters and the China coastal water. The fourth EOF mode accounts for 5.4% of total variance and reveals cold eddies around Chusan Islands. The temporal variance EOF analysis is less revealing in this study area. ( 2000 Elsevier Science Ltd. All rights reserved.

Keywords: East China Sea; NOAA/AVHRR; SST; EOF analysis; Kuroshio; Satellite remote sensing

* Corresponding author.

1. Introduction

The East China Sea (ECS) is a broad continental shelf bounding the North Paci"c Ocean in the west (see Fig. 1). It is connected to the Yellow Sea (YS) in the north and the South China Sea (SCS) in the south through the Taiwan Strait. The broad shelf of ECS, covering an area of about 770,000 km, is bounded seaward by the 200 m isobath extending from northeast Taiwan to southern Japan (Fig. 1). Farther seaward is the steep continental slope over which the Kuroshio #ows. Major surface features of ECS include the Kuroshio Current (KC), the Kuroshio Branch Current (KBC), the Taiwan Warm Current (TWC), the China Coastal water (CCW), the Changjiang (Yangtze River) water and the Yellow Sea mixed cold water. The temporal and spatial variations of these systems and interactions among them are a!ected mainly by the East Asian monsoon. In addition, bottom topographic features may also modulate

Fig. 1. East China Sea and vicinity. Isobaths are in meters. C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 375 the structures of thermohaline fronts, cold eddies, meanders and thermocline depths (Miao and Yu, 1991). Distributions of nutrients, planktons, chlorophyll-a, dissolved oxygen, "sh larvae and species are a!ected by these mesoscale features. In recent years, two interdisciplinary research projects including the KEEP (Kuroshio Edge Exchange Processes) series initiated by Taiwan and the `China}Japan Joint Investigation and Study on the Kuroshioa have been conducted. Physical and biogeochemical data provide a "rst-order description of basic processes at work. These processes include the seasonal variation of the Kuroshio main axis and its relation to fronts and eddies, and the Kuroshio countercurrent variation in relation to intrusions of Kuroshio subsurface waters onto ECS o! northeast Taiwan (Sun and Pan, 1987; Qiu et al., 1990; Chao, 1991; Lin et al., 1992; Tang and Wen, 1994). Furthermore, the dispersal of Changjiang River plume and associated suspended sediments into ECS has been reported by Beardsley et al. (1985). The Changjiang runo! and distributed freshwater discharge from China often form a narrow band of cold waters shoreward of the 50 m isobath (Pan et al., 1991a,b). The origin and axis variation of TWC was also documented by in situ hydrographic data (Pan et al., 1987). It was also found that the Yellow Sea mixed cold waters often intrude southward into ECS and interact with the Kuroshio to form fronts, eddies, meanders, and cold and warm core rings (Zheng and Klemas, 1982; Yuxiang, 1996). Lacking synopticity covering the entire ECS, major components of KEEP studies mainly concentrated on regional dynamics in the southern portion of ECS. The present study complement their e!orts by providing a synoptic view of the entire ECS. We utilize a time series of sea surface temperature (SST) images obtained from synoptic view NOAA weather satellite advanced very high resolution radiometer (AVHRR) to examine the relation between SST and regional processes reported earlier or in the KEEP series special issue. Moreover, the EOF analysis was used to decompose the multidimensional data into modes ranked by their variance. From those EOF modes, we could identify the dominant feature components in the study area. In the past decades, the EOF method had been applied to analyze the AVHRR/MCSST sea surface temperature images sequence to examine some ocean processes, such as large- and mesoscale current systems (Gallaudet and Simpson, 1994), upwelling and cold eddies (Fang and Hsieh, 1993), seasonal and annual SST variability (Chiswell, 1994; Yu and Emery, 1996) and meander propagation (Everson et al., 1997), etc. This method will be discussed brie#y in the next section.

2. Material and methods

2.1. NOAA/AVHRR SST images

The NOAA/HRPT (High Resolution Picture Transmission) station of the Satellite Remote Sensing Laboratory in Taiwan Fisheries Research Institute (TFRI) is located in Keelung, Taiwan (location: 25.13N, 121.73E; height: 25 m above sea level). The station operates daily to receive and process the NOAA/AVHRR data. In the study period (1994/10}1996/09), SST "elds of ECS were available from NOAA-9, 12 and 14 376 C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387

Table 1 The characteristics of NOAA/AVHRR (Advanced Very High Resolution Radiometer)!

Channel No. Wavelength (lm)

Visible 1 0.58}0.68 2 0.725}1.1 Infrared 3 3.55}3.93 4 10.3}11.3 5 11.5}12.5

IFOV at nadir 1.1 k;1.1 km Swath width 2580 km NEDT 0.123C Height of orbit 850 km

!IFOV: Instantaneous "eld of view. NEDT: Noise equivalent di!erential temperature. satellites. The AVHRR carried aboard the NOAA polar orbiting satellites is equipped with a "ve-channel sensor in the visible and infrared wavebands. Table 1 shows the main characteristics of the AVHRR (Lauritson et al., 1979). The AVHRR data are extracted from the raw HRPT telemetry data to calculate the digital SST images by using the MultiChannel Sea Surface Temperature (MCSST) method (Strong and McClain, 1984; McClain et al., 1985). Those SST images are in 1.1;1.1 km resolution (IFOV at nadir) and its noise equivalent di!erential temperature (NEDT) is approximately 0.123C. During this study, hundreds of images were processed and 262 MCSST images that are mostly cloud-free were selected. Fig. 1 shows the topography of the East China Sea and geographical covering area of satellite image in this study. It is centered at 283N, 1253E and covers an area of approximately 970 km;880 km (880;800 pixels). All of the 262 images were used to analyze the temporal}spatial variations of surface features in this area.

2.2. EOF analysis

In this study, the monthly SST images were utilized to extract dominant surface features through EOF analysis. Available cloud-free images in each month are averaged pixel by pixel to derive the monthly mean SST. In order to interpret the di!erence between, and suitability of, temporal and spatial variances, EOF is per- formed by two methods (Lagerloef and Berstein, 1988; Eslinger et al., 1989; SeaSpace, 1992; Gallaudet and Simpson, 1994; Kawamara, 1994). First, all SST images were pre-processed by removing the temporal average of all monthly images. The expres- sion is given as follows: 1 , I(x, t)"I(x, t)! + I(x, t), (1) N R C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 377 where I(x, t) represents the set of all monthly images, I(x, t) is the set of all demeaned monthly images, and N is the number of all monthly images. Using EOF analysis the demeaned monthly images, 24 in total, produce the temporal variance. Alternatively, the spatial average of each image can be removed as follows:

1 + I(x, t)"I(x, t)! + I(x, t), (2) MV where M is the total pixel number of every image. The spatial variance can then be examined using EOF analysis. The spatially or temporally demeaned I(x, t) set is used to calculate the auto- variance of each image and the covariance between images. An eigenvector aL(t)is then obtained to decompose I(x, t) as follows: , " + I (x, t) aLFL(x), (3) L The time-varying amplitude function, aL(t), is calculated by the projection method using the formula: + " + aL(t) I (x, t)FL(x). (4) R In Eqs. (3) and (4), FL(x) is the spatial amplitude function of each EOF mode to be used to facilitate a comparison with dominant hydrographic distribution patterns in ECS. In addition, a spectral analysis of aL(t) gives the dominant periodicity of those EOF modes.

3. Results and discussion

3.1. Patterns in summer

Fig. 2 shows a time series of SST images in the summer of 1995 and 1996. The average SST over the ECS is about 27}293C during the summer. Isotherms are mostly parallel to isobaths, running in the southwest}northeast direction. Three cold areas are evident, including the seaward Changjiang runo!, the coastal waters of China and the region o! northeast Taiwan. Speci"cally, the cold water associated with Chang- jiang runo! covers the widest area and contains the strongest SST gradient. The maximum temperature de"cit exceeds 53C inside this patch in the East China Sea. Summer is the runo! season. According to Pan et al. (1997), the average discharge of the Changjiang is about 10,000 m/s in winter and 50,000 m/s in summer. Furthermore, ECS is dominated by southwest monsoon during the summer. The upwelling-favor- able winds tend to disperse Changjiang runo! seaward through Ekman transports, resulting in an expansive plume. In addition, Chinese oceanographers observed that the subsurface water of the Taiwan Warm Current coming out of the Taiwan 378 C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387

Strait would turn seaward near 293N in summer. This phenomenon might cause the coastal subsurface water to upwell, enhancing the cold anomaly o! Changjiang River (Beardsley et al., 1985). Farther southward, Fig. 2 reveals the presence of cold eddies o! northeast Taiwan in summer (especially in the plate B, C and D), consistent with earlier "ndings (Lin et al., 1992; Sun and Xiu, 1997). The KEEP researchers also concluded that the Kuroshio subsurface water intrudes onto ECS shelf to manifest subsurface eddies o! northeast Taiwan (Chern and Wang, 1989; Tang and Wen, 1994). This intrusion is a year-round feature. However, this feature is capped by a thermal layer due to excessive solar insolation in summer, and is therefore not very visible from SST images. Fig. 2 also gives a distinct impression that the would-be southward excursion of Changjiang plume is blocked by the warm water mass over the ECS. Numerical

Fig. 2. Main surface features around the East China Sea in summer, derived from NOAA/AVHRR monthly averaged SST images. The four months include 1995/07, 1995/08, 1996/07 and 1996/08. C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 379 simulations (Chao, 1991) lend support to this scenario. Under the southwest monsoon, the circulation over the mid-shelf is northward, pushing the plume water northward. Moreover, Beardsley et al. (1985) also reported that the Changjiang diluted water #ows mainly to the northeast in summer. Distributions of "sh species are largely a!ected by nutrients, chlorophyll-a, planktons, temperature, salinity and ocean color in areas of cold SST. Chao (1993) surveyed the in situ ocean color and found high suspended sediment concentrations in the southwestern portion of Changjiang plume. In addition, Lin et al. (1994) found good correlation between catches of large purse-seine "shes and the strength of the cold eddies in waters o! northeast Taiwan. Generally, cold water areas are important "shing grounds due to higher nutrients concentration and higher primary produc- tivity.

3.2. Patterns in winter

Fig. 3 shows the dominant SST features of ECS in the winter of 1994, 1995 and 1996. The time series of SST reveal that the surface axis of the Kuroshio Current moves westward under the northeast monsoon in winter. The intrusion of subsurface Kuroshio waters onto ECS shelf o! northeast Taiwan also becomes evident in winter. Sun and Pan (1987) and Hsueh et al. (1992) indicated that the Kuroshio Current axis moved closer toward the shelf from late fall to next spring and then shifted seaward again in summer. O! northeast Taiwan, the shelfbreak as indicated by the 200 m isobath is zonal, almost perpendicular to the incoming Kuroshio Current from the south. As the Kuroshio impinges on the shelfbreak, meanders and eddies are gener- ated, resulting in a seaward de#ection of the Kuroshio front and associated cold eddies (Chern and Wang, 1990; Lin et al., 1992; Tang and Wen, 1994). After passing the northeast Taiwan, the Kuroshio Current continues to #ow northeastward along the 200 m isobath. The Kuroshio water interacts with the mid-shelf water of ECS and the Yellow Sea mixed cold water to form fronts, meanders, countercurrent and some eddies (Zheng and Klemas, 1982; Sugimoto et al., 1988). Zonally, the strongest SST gradient of the Kuroshio front is about 53C per 30 nm (nautical miles) at 303N and 1273E in April or May each year. This might be related to the fact that the Yellow Sea mixed cold water expanding southward to reach ECS shelf and to interact with the Kuroshio Current. Fig. 3b shows that the Kuroshio Current intruded onto ECS shelf preferably at two locations in winter. One is at the shelfbreak o! northeast Taiwan, where the meander and eddies are evident. Another location is near 313N and 1283E; previous works have identi"ed this location as the origin of the Tsushima Current (Huh, 1982). Strong northeast monsoon and steep bottom topographies may contribute to the intrusion at the two preferred sites. As rains diminish in winter, there is less freshwater runo! from China. Aided by the northeast monsoon, the freshwater boundary layer expands southward to form a narrow band of cold waters along the coast of China. This coastal cold area is mainly con"ned landward of the 50 m isobath. The cross-shore SST gradient associated with the cold water band appears to increase with the strength of the northeast monsoon. The cold water along the western boundary of ECS extends southeastward 380 .Tege al. et Tseng C. / otnna hl eerh2 20)373 (2000) 20 Research Shelf Continental } 387

Fig. 3. Main surface features around the East China Sea in winter, derived from NOAA/AVHRR monthly averaged images. Months include 1994/10, 1995/01, 1995/03, 1995/11, 1996/01 and 1996/03. C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 381 to the middle reaches of the Taiwan Strait. Cold waters also appear in the nearshore area on the east side of the Taiwan Strait. The Yellow Sea mixed cold water expands southward into ECS shelf in winter. Time series of SST images suggest that the southward expansion reaches maximum in April each year. The 153C-isotherm extends as far south as 293N over the ECS shelf. The expansion would carry suspended sediments from the northern Yellow Sea to ECS and would interact with the Kuroshio Current to induce fronts, eddies, countercurrent and meanders (Shibata, 1983).

3.3. EOF analysis of SST xelds

Leaving snapshots aside, more can be learned about the periodicity of the system by a spectral analysis. The empirical orthogonal function (EOF) is utilized to analyze the surface principal component images (EOF modes) in the northwestern ECS, with emphases on the Changjiang plume. Fig. 4 shows the variance percentage of all EOF modes derived from the spatial and temporal variance of EOF analysis from the 24 monthly SST images from October 1994 to September 1996. The "rst 4 modes are adequate to express dominant surface features in the northwestern ECS. In the spatial variance EOF analysis, the "rst mode accounts for 47.4% of spatial variance. It contains the structure of Changjiang plume; isotherms are otherwise more or less parallel to the isobath (Figs. 1 & 5 (A)). The time-varying amplitude function

Fig. 4. Variance percentage and cumulative variance percentage of all modes derived from the spatial and temporal variance EOF analysis of 24 monthly SST images (from October 1994 to September 1996). 382 C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387

Fig. 5. Images of the "rst four modes derived from the spatial variance EOF analysis. The "rst mode accounts for 47.4% and the second mode account for 16.4% of the total variance. C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 383

(Fig. 6(A)) suggests that the "rst mode occurs mainly in winter. The second and third modes account for 16.4 and 9.6% of the spatial variance, respectively (Fig. 4). They contain the China coastal water extending southward along the coast and the Yellow Sea mixed cold water intruding into ECS shelf in winter (Figs. 5(B), 5(C) and 6(B), (C). The coastal front separates the China coastal water from the mid-shelf ECS water. The fourth mode accounts for 5.2% of the spatial variance (Fig. 4). This mode occurs mainly in summer based on its time-varying amplitude function (Fig. 6(D)) and reveals the cold water pattern in the southeastern portion of Changjiang plume. The dominant periodicity for the "rst three modes is annual; only the fourth mode has a semi-annual cycle. Fig. 4 also shows the variance percentage of all temporal EOF modes. The cumulative percentage of the "rst four modes is more than 90% in the temporal variance EOF analysis, enough to explain the dominant surface features. Fig. 7 shows the "rst four principal component images derived from the temporal variance EOF analysis. Corresponding time-varying amplitude functions are shown in Fig. 8. The "rst EOF mode accounts for 77.4% of the temporal variance. It contains the narrow band of cold waters shoreward of the 50 m isobath and the Yellow Sea mixed cold water intruding onto ECS shelf in winter (Figs. 7(A) and 8(A)). The second EOF mode accounts for 11.2% of the temporal variance. This mode contains the strong coastal thermal gradient (fronts) in winter (Figs. 7(B) and 8(B)). Modes higher than the third

Fig. 6. Time-varying amplitude functions corresponding to Fig. 5 for the "rst four modes derived from the spatial variance EOF analysis. 384 C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387

Fig. 7. Images of the "rst four modes derived from the temporal variance EOF analysis. The "rst mode accounts for 77.4% and the second mode accounts for 11.2% of the total variance. C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387 385

Fig. 8. Time-varying amplitude functions corresponding to Fig. 7 for the "rst four modes derived from the temporal variance EOF analysis.

do not exhibit any dominant surface feature in the northwestern ECS. The "rst mode has an annual cycle and the second mode contains a semi-annual periodicity. Kelly (1985) and Chiswell (1994) indicated that the spatial variance EOF analysis is better suited when the SST gradients are pronounced. The study area is rich in fronts, eddies and meanders, and the spatial EOF analysis is conceivably better. Not surprisingly, the "rst four modes from the spatial variance EOF analysis are able to contain all dominant surface features in ECS.

4. Conclusions

Satellite remote sensing techniques prove to be an important tool for providing a synoptic view of SST in ECS with improved spatial and temporal resolutions. In this study, the NOAA/AVHRR sea surface temperature images were examined to extract surface features over the ECS shelf. The results help to clarify dominant surface features by a qualitative analysis and essential seasonal variations by a quantitative EOF analysis. In summer, two dominant cold eddies were found o! northeast Taiwan and to the south of Changjiang mouth. Between the two eddies, the eddy to the south of the Changjiang mouth (near Chusan islands) is the more pronouced, characterized by a large SST anomaly covering an area larger than 12,000 km. In winter, the 386 C. Tseng et al. / Continental Shelf Research 20 (2000) 373}387

Kuroshio Current intrudes onto ECS shelf o! northeast Taiwan. Further, the Yellow Sea mixed cold water expands southward over the mid-shelf of ECS and interacts with the Kuroshio to form fronts, meanders and eddies. The "rst spatial EOF mode accounts for 47.4% of total spatial variance and reveals the Changjiang plume and coastal cold waters o! China. The "rst temporal EOF mode accounts for 77.4% of total variance and its eigenvector is similar to the overall SST pattern of ECS. The second and third modes account for 10.4 and 3.1% of total variance and indicate coastal frontal features. As more in-situ observational data become available in the future, an intercomparison with SST images will become increasingly important in order to further our understanding of ECS circulation.

Acknowledgements

This study was sponsored by the National Science Council (NSC), Republic of China (Project code: NSC85-2611-M-056-001-K2). The authors wish to thank Dr. I. C. Liao, Director General of Taiwan Fisheries Research Institute, for his assistance and supports. We also thank Dr. S. Y. Chao (University of Maryland) for providing editorial comments.

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